Centre for Longitudinal Studies

Find out more about the level of response for every sweep of the 1958 National Child Development Study, important predictors of non-response, and how to handle missing data in the study.

As of September 2026:

  • Of the 17,415 cohort members who participated in the first sweep, 3,898 (22.4%) have participated in all 12 major sweeps.
  • Of all 18,558 cohort members, 12,619 (68.0%) have taken part in at least half the sweeps (six or more sweeps).

NCDS response (1958-2020)

The table below presents statistics about response in NCDS at every major sweep from birth.

Table: Participation in NCDS from birth to 62 years

Total cohortDeadEmigrantsEligible sampleParticipants(% of eligible sample)
Birth – 195817,6330017,63317,41598.8
Age 7 – 196518,010a82147516,71415,42592.3
Age 11 – 196918,283a84070116,74215,33791.6
Age 16 – 197418,558a87379916,88614,65486.8
Age 23 – 198118,5589601,19616,40212,53776.4
Age 33 – 199118,5581,0491,33516,17411,46970.9
Age 42 – 200018,5581,1991,26816,09111,41971.0
Age 44 – 200218,5581,2861,23616,0369,37758.5
Age 46 – 200418,5581,3231,27215,9639,53459.7
Age 50 – 200818,5581,4591,29315,8069,79061.9
Age 55 – 201318,5581,6591,28615,6139,13758.5
Age 62 – 202018,5582,4471,526b14,585b8,215b56.3

a At ages 7, 11 and 16, the original sample was supplemented by migrants born in 1958.

b At age 62, 327 cohort members known to be living outside of Great Britain (emigrant cases) were invited to take part in the mop-up web survey, of whom 190 responded. Such emigrants are not formally considered as part of the NCDS target population, so to maintain consistency with earlier sweeps they have been considered as ineligible in these calculations (and those preceding the table), though their data are available for analysis.

Figure 1: NCDS response (as % of eligible sample) over time

Missingness in NCDS

Missing data are common in surveys and cohort studies. To tackle this in NCDS, we have used a systematic data-driven approach to identify variables that are important predictors of non-response at each sweep.

We have used a systematic data-driven approach to identify variables that are important predictors of non-response at each NCDS sweep, between age seven and age 55. Future work will extend this analysis to include non-response at the age 62 sweep.

A list of these variables is provided in the appendix of the Handling missing data in the CLS cohort studies user guide.

These variables can then be considered for inclusion in analyses – for example as auxiliary variable when using multiple imputation – in order to maximise the plausibility of the missing at random (MAR) assumption.

Read more about the process in the article: Missing at random assumption made more plausible: evidence from the 1958 British birth cohort.

Example: restoring the composition of NCDS at age 50 and 55

We have been able to restore the composition of the NCDS samples at ages 50 and 55 to be more representative of the study’s target population. We did this by including predictors of non-response at age 50 and age 55 as auxiliary variables in multiple imputation analyses.

For example, we were able to replicate:

  • the original distribution of paternal social class observed at the birth survey
  • the distribution of cognitive ability at age seven
  • the known population distribution of educational attainment and marital status at age 50.

Figure 2: Social class of mother’s husband at birth before and after adjustment for missing data

Graph showing social class of mother’s husband at birth before and after adjustment for missing data.

The imputation phase of this analysis included predictors of non-response at age 55 and social class at birth only for cohort members that participated at age 55.

Figure 3: Percentage of those with degree or equivalent at age 50 in the Annual Population Survey and NCDS before and after adjustment for missing data.

: Percentage of those with degree or equivalent at age 50 in the Annual Population Survey and NCDS before and after adjustment for missing data.

APS GB: Annual Population Survey = Born in Great Britain in 1958, derived by the Office for National Statistics (ONS)

APS All: Annual Population Survey = Born in Great Britain or elsewhere in 1958 (derived by ONS)

NCDS50 MI: Estimate after multiple imputation using predictors of educational attainment at age 50 and predictors of non-response at age 50 as auxiliary variables.

Useful documents

Narayanan, M.K., Dodgeon, B., Katsoulis, M., Ploubidis, G.B. & Silverwood, R.J. (2024)

How to mitigate selection bias in COVID-19 surveys: evidence from five national cohorts

European Journal of Epidemiology

Rajah, N., Calderwood, L., De Stavola, B.L., Harron, K., Ploubidis G.B. & Silverwood, R.J. (2023)

Using linked administrative data to aid the handling of non-response and restore sample representativeness in cohort studies

BMC Medical Research Methodology

Silverwood, R.J., Goodman, A., Ploubidis, G.B. (2022)

Letter to the editor: Don’t forget survey data: ‘healthy cohorts’ are ‘real-world’ relevant if missing data are handled appropriately

Longitudinal and Life Course Studies

Mostafa, T., Narayanan, M., Pongiglione, B., Dodgeon, B., Goodman, A., Silverwood, R.J., & Ploubidis, G.B. (2021)

Missing at random assumption made more plausible: evidence from the 1958 British birth cohort

Journal of Clinical Epidemiology